Deep Neural Networks (DNNs) are a state-of-the-art technique in many recognition tasks such as object and speech recognition. DNNs comprise a feed-forward arrangement of layers each exhibiting high computational demands and parallelism which are commonly exploited with the use of Graphic Processing Units (GPUs). The high computation demands of DNNs and the need for higher energy efficiency has motivated the development and proposal of special purpose architectures. However, power continues to be a limiting factor in DNN designs.
Accordingly, there remains a need for improvements in the art.